German Wiener Sachtextformel

Wiener Sachtextformel: the standard German readability index

Computes the Wiener Sachtextformel (WSTF first formula) from your German text, using the share of 3+ syllable words, average sentence length, share of long words and share of one-syllable words. Returns a school-grade readability level from 4 to 15.

What is the Wiener Sachtextformel?

It is the standard readability formula for German non-fiction, developed by Richard Bamberger and Erich Vanecek. The result is a number that corresponds roughly to the German school grade needed to understand the text.

The German Wiener Sachtextformel tool computes the WSTF — the de facto standard readability index for German non-fiction. Unlike English formulas, it is calibrated on German texts, so it handles German’s long compound words correctly. The output is a number that maps to the German school grade a reader needs to understand the passage.

How it works

The tool tokenises your text into sentences and words, counts syllables per word, and computes four predictors as percentages of the total word count (except sentence length):

  • MS — percentage of words with 3 or more syllables.
  • SL — average sentence length (words ÷ sentences).
  • IW — percentage of words with more than six letters.
  • ES — percentage of words with exactly one syllable.

It then applies the first Wiener Sachtextformel:

WSTF = 0.1935·MS + 0.1672·SL + 0.1297·IW − 0.0327·ES − 0.875

Syllables are counted by the vowel-nucleus method (each maximal vowel run = one syllable), the same approach used by the German Syllable Counter.

Interpreting the score and notes

The result is a grade-like number, roughly 4 to 15. As a guide: 4–6 reads as easy primary-school text, 7–10 suits general adult readers, 11–12 is demanding, and 13–15 is difficult academic or technical German. For broad public communication, aim below 6. Scores are most reliable on passages of at least a few sentences; very short inputs make SL and the percentages unstable. The formula treats abbreviations and numerals loosely, so review automatically generated scores on heavily numeric text.